Valve, makers of Steam, talks about their pricing experiments: "Without making announcements, we varied the price ... pricing was perfectly elastic ... Then we did this different experiment where we did a sale ... a highly promoted event ... a 75 percent price reduction ... gross revenue [should] remain constant. Instead what we saw was our gross revenue increased by a factor of 40. Not 40 percent, but a factor of 40 ... completely not predicted by our previous experience with silent price variation." [[1]]

An idea whose time has come, profiling code based not on the execution time required, but the power consumed ([1])

Grumpy about work and dreaming about doing a startup? Some food for thought for those romanticizing startup life. ([1][2])

Yahoo discovers toolbar data (the urls people click on and browse to) helps a lot for web crawling ([1])

Google Personalized Search adds explanations. Explanations not only add credibility to recommendations, but also make people more accepting of recommendations they don't like. ([1])

"Until now, many education studies have been based on populations of a few dozen students. Online technology can capture every click: what students watched more than once, where they paused, what mistakes they made ... [massive] data ... for understanding the learning process and figuring out which strategies really serve students best." ([1])

Andrew Ng's machine learning class at Stanford was excellent; I highly recommend it. If you missed it the first time, it is being offered again (for free again) next quarter. ([1])